Fourier Transform: Definition, Calculation & Verification

In summary, the conversation discusses the use of the Fourier transform with a specific definition and a given function. The correct answer is provided and the conversation also mentions the use of inverse Fourier transform and the operation of shifting and broadening a pulse in the frequency domain. The individual is grateful for the help and can now successfully tackle some questions related to Fourier transforms.
  • #1
Benny
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Hi, I'm using the following definition for the Fourier transform.

[tex]
F\left( q \right) = \int\limits_{ - \infty }^\infty {e^{iqx} f\left( x \right)dx}
[/tex]

(I used a capital F instead of f with a squiggle on top because the tex code doesn't seem to be working the way I intended it to.)

I have the function

[tex]
f\left( x \right) = \left\{ {\begin{array}{*{20}c}
{1,a < x < b} \\
{0,otherwise} \\
\end{array}} \right.
[/tex]

So [tex]F\left( q \right) = \int\limits_{ - \infty }^\infty {e^{iqx} f\left( x \right)dx} [/tex]

[tex] = \int\limits_a^b {e^{iqx} dx} [/tex]

[tex]
= \frac{i}{q}\left( {e^{iqa} - e^{iqb} } \right)
[/tex]

According to the definition I'm using, is this the correct answer? I ask this because I'm not given an answer and I need to verify my answer by using the inverse Fourier transform. I haven't done complex analysis so integrals of ratios of exponentials and polynomials aren't things I can deal with right now. Which is why I'd like to know if I've taken the correct approach so that I can at least get through some questions.

Any help would be good thanks.
 
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  • #2
Yes, that's correct. You can rewrite that if you want as something like [itex]e^{iq(b+a)/2}\sin(q(b-a))/q[/itex] (that's probably not exactly right). Remember that the Fourier transform of unit length square pulse centered at t=0 is a sinc function (sin(x)/x), with some extra normalization factors. Then you just need to shift and broaden this pulse to get a square pulse extending from t=a to t=b. Do you remember the frequency domain operations corresponding to shifting and broadening a pulse in time?
 
  • #3
I've only just started on Fourier transforms so I don't know too much about them.Thanks for your help though, at least I can get through some questions now.
 

FAQ: Fourier Transform: Definition, Calculation & Verification

1. What is the Fourier Transform and why is it important in science?

The Fourier Transform is a mathematical operation that decomposes a signal or function into its constituent frequencies. It is important in science because it allows us to analyze signals and understand their frequency components, which is essential in many fields such as engineering, physics, and digital signal processing.

2. How is the Fourier Transform calculated?

The Fourier Transform is calculated using an integral equation that involves complex numbers and trigonometric functions. This equation is solved for each frequency component, resulting in a spectrum that represents the signal in the frequency domain.

3. What is the relationship between the Fourier Transform and the Inverse Fourier Transform?

The Fourier Transform and Inverse Fourier Transform are essentially the same operation, but in opposite directions. The Fourier Transform converts a signal from the time domain to the frequency domain, while the Inverse Fourier Transform converts it back from the frequency domain to the time domain.

4. How is the accuracy of a Fourier Transform verified?

The accuracy of a Fourier Transform can be verified by comparing the results to known or expected values for the signal. It can also be checked by using different algorithms or techniques for the calculation and comparing the results.

5. What are some common applications of the Fourier Transform?

The Fourier Transform has numerous applications in science and engineering. Some common uses include signal processing, image processing, data compression, and solving differential equations. It is also used in many fields such as astronomy, acoustics, and optics for analyzing and understanding various physical phenomena.

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